Nothing
rbenchmark <- function( m, n=2, k=n, segments=NULL, x.t=1,
margins=c( "unif", "beta", "exp", "frechet", "gamma",
"gev", "gpd", "gumbel", "lnorm", "logis",
"norm", "weibull"), ... )
{
###
### This function generates m long only random portfolios with n investments where
### weights are between given lower and upper bound and the sum of
### the weights equals a given total sum. Results are return as a matrix
###
### Arguments
### m = a positive integer value for the number of portfolios to be generated
### n = a positive integer value for the number of investments in a portfolio
### k = a positive integer value for the number of non zero weights
### segments = a list or vector of investment indices that define portfolio segments
### x.t = a numeric value for the sum of the investment weights
### margins = a character value for the marginal distribution of the truncated variates
### ... = additional arguments passed to the random variable function for the margin
###
if ( missing( m ) )
stop( "Argument 'm' is missing" )
if ( m <= 0 )
stop( "Argument 'm' is not positive" )
###
### private function
###
by.case <- function( case, number, size, theseSegments, total, marginals, ...)
{
return( random.benchmark( n=number, k=size, segments=theseSegments, x.t=total,
margins=marginals, ... ) )
}
weights <- t( sapply( 1:m, by.case, n, k, segments, x.t, margins, ... ) )
if ( n == 1 ) {
weights <- t( weights )
}
return( weights )
}
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